This article describes six key decisions that must be made while crafting the ETL architecture for a dimensional data warehouse. These decisions have significant impacts on the upfront and ongoing cost and complexity of the ETL solution and, ultimately, on the success of the overall BI/DW solution. Read on for Kimball Group’s advice on making […]

A student in a recent Data Warehouse Lifecycle in Depth class asked me for an overview of the Kimball Lifecycle approach to share with their manager. Confident that we’d published an executive summary, I was happy to oblige. Much to my surprise, our only published Lifecycle overview was a chapter in a Toolkit book, so this Design Tip […]

A junk dimension combines several low-cardinality flags and attributes into a single dimension table rather than modeling them as separate dimensions. There are good reasons to create this combined dimension, including reducing the size of the fact table and making the dimensional model easier to work with. Margy described junk dimensions in detail in Kimball Design Tip #48: […]

A student attending one of Kimball Group’s recent onsite dimensional modeling classes asked me for a list of “Kimball’s Commandments” for dimensional modeling. We’ll refrain from using religious terminology, but let’s just say the following are not-to-be-broken rules together with less stringent rule-of-thumb recommendations. Rule #1: Load detailed atomic data into dimensional structures. Dimensional models […]

Successful data warehouse and business intelligence solutions provide value by helping the business identify opportunities or address challenges. Obviously, it’s risky business for the DW/BI team to attempt delivering on this promise without understanding the business and its requirements. This Design Tip covers basic guidelines for effectively determining the business’s wants and needs. First, start by properly preparing […]